Biologically Inspired Neural & Dynamical Systems (BINDS) Laboratory
University of Massachusetts Amherst

The postdoc work will be concentrating on:
How memories are modified, what other systems take part of it, how can the system benefit from changing memories?
These questions are asked from the functional and computational view, and will be tackled using theories of dynamical systems, knowledge of neurobiology and memory system, mathematical analysis and control. The modeling created will then be transferred into crisp principles and from there to machine learning, detection, and navigation.
The successful candidate will have a Ph.D. in Computer Science, Cognitive Science, Psychology, Engineering or a related field.
Excellent programming skills in C++ and Matlab, knowledge of machine learning, and deep analytical knowledge and skills.
The initial appointment will be for one year and renewable based performance and funding.
The position is open immediately and salary is standard for computer science.
Applicants should send a cover letter, a CV, representative publications, and the names of three references directly to Hava Siegelmann

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